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A pre-feasibility study of wind resources in Kutubdia Island, Bangladesh

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  • Khadem, Shafiuzzaman Khan
  • Hussain, Muhtasham

Abstract

Kutubdia is one of the coastal islands in Bangladesh. The wind speed data at the wind monitoring station of Bangladesh Meteorological Department (BMD), Kutubdia, located in a built-up area, appears to be low, but at another location, near the seashore, Bangladesh Centre for Advanced Studies (BCAS) finds that the wind energy availability should be reasonably high. Considering the surface roughness, obstacle condition and terrain information of the island, a micro-scale prediction has been done using (100×100m2) grid cells in the Wind Atlas Analysis and Application Program (WAsP) to develop monthly and annual wind atlas and also a wind resource map which shows that at 50m height, the annual wind speed over Kutubdia coast varies from 5.1 to 5.8m/s. Southern and Eastern sides of Kutubdia appear to be promising for wind electricity generation using large turbines where wind power density at a height of 50m or higher is found to be above 200W/m2 annually over the year September 1996 to August 1997. It is found that at 30m height, the coast side of Kutubdia should be sustainable for small turbines.

Suggested Citation

  • Khadem, Shafiuzzaman Khan & Hussain, Muhtasham, 2006. "A pre-feasibility study of wind resources in Kutubdia Island, Bangladesh," Renewable Energy, Elsevier, vol. 31(14), pages 2329-2341.
    • Handle: RePEc:eee:renene:v:31:y:2006:i:14:p:2329-2341
    DOI: 10.1016/j.renene.2006.02.011
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    References listed on IDEAS

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    1. Sarkar, M. & Hussain, M., 1991. "The potential of wind electricity generation in Bangladesh," Renewable Energy, Elsevier, vol. 1(5), pages 855-857.
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    Cited by:

    1. Carta, José A. & Velázquez, Sergio & Cabrera, Pedro, 2013. "A review of measure-correlate-predict (MCP) methods used to estimate long-term wind characteristics at a target site," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 362-400.
    2. Ahmed, Ahmed Shata, 2012. "Potential wind power generation in South Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1528-1536.
    3. Xiao Liu & Xu Lai & Jin Zou, 2017. "A New MCP Method of Wind Speed Temporal Interpolation and Extrapolation Considering Wind Speed Mixed Uncertainty," Energies, MDPI, vol. 10(8), pages 1-21, August.
    4. Montes, German Martinez & Martin, Enrique Prados & Bayo, Javier Alegre & Garcia, Javier Ordoñez, 2011. "The applicability of computer simulation using Monte Carlo techniques in windfarm profitability analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4746-4755.
    5. Sharma, Kaushik & Ahmed, M. Rafiuddin, 2016. "Wind energy resource assessment for the Fiji Islands: Kadavu Island and Suva Peninsula," Renewable Energy, Elsevier, vol. 89(C), pages 168-180.
    6. Mondal, Md. Alam Hossain & Denich, Manfred, 2010. "Assessment of renewable energy resources potential for electricity generation in Bangladesh," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(8), pages 2401-2413, October.
    7. Chang, Byungik & Starcher, Ken, 2019. "Evaluation of wind and solar energy investments in Texas," Renewable Energy, Elsevier, vol. 132(C), pages 1348-1359.
    8. Salehin, Sayedus & Ferdaous, M. Tanvirul & Chowdhury, Ridhwan M. & Shithi, Sumaia Shahid & Rofi, M.S.R. Bhuiyan & Mohammed, Mahir Asif, 2016. "Assessment of renewable energy systems combining techno-economic optimization with energy scenario analysis," Energy, Elsevier, vol. 112(C), pages 729-741.
    9. Abul Kalam Azad & Mohammad Golam Rasul & Talal Yusaf, 2014. "Statistical Diagnosis of the Best Weibull Methods for Wind Power Assessment for Agricultural Applications," Energies, MDPI, vol. 7(5), pages 1-30, May.
    10. Majbaul Alam & Subhes Bhattacharyya, 2016. "Decentralized Renewable Hybrid Mini-Grids for Sustainable Electrification of the Off-Grid Coastal Areas of Bangladesh," Energies, MDPI, vol. 9(4), pages 1-16, April.
    11. Gugliani, G.K. & Sarkar, A. & Ley, C. & Mandal, S., 2018. "New methods to assess wind resources in terms of wind speed, load, power and direction," Renewable Energy, Elsevier, vol. 129(PA), pages 168-182.

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